How to Use the Dagster MCP in AutoGen

Q: How do I register the Dagster MCP Server with AutoGen?

Install autogen-extmcp and use the mcpservertools function with your Vinkius HTTP URL for Dagster. Pass the resulting tool list directly to your AutoGen AssistantAgent.

Let your AutoGen agents debate and resolve Dagster pipeline failures using this MCP Server.

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Connect Dagster MCP to AutoGen

Create your Vinkius account to connect Dagster to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Dagster with AutoGen

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Resolve Dagster pipeline failures through AutoGen debate

The `get_run` tool fetches detailed Dagster failure logs for your AutoGen debugging agent. A separate AutoGen critic agent reviews the log output and challenges the initial Dagster diagnosis. By analyzing the Dagster run details, the AutoGen agents agree on whether the failure was caused by a database timeout. They present a single, consensus-driven Dagster resolution path to your team.

Audit Dagster schedules with an AutoGen MCP Server

The `list_schedules` tool provides the active Dagster cron configurations to your AutoGen scheduling agent. Meanwhile, your AutoGen validation agent uses `list_sensors` to verify if the corresponding Dagster triggers are active. The AutoGen agents negotiate to find Dagster discrepancies, such as an active schedule pointing to a disabled sensor. They compile these Dagster findings into a clean report.

Map Dagster data lineage across AutoGen agents

The `list_assets` tool outputs your software-defined Dagster asset definitions to your AutoGen mapping agent. An AutoGen performance agent simultaneously calls `list_jobs` to correlate these assets with active Dagster execution paths. They collaborate within the AutoGen group chat to trace how a delay in an upstream Dagster asset affects downstream jobs. This multi-agent coordination ensures you get a complete view of your Dagster health.

Setup guide

Set up Dagster MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Dagster tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Dagster_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Dagster data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Dagster_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Dagster data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Dagster. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Dagster MCP in AutoGen

Install autogen-ext[mcp] and use the mcp_server_tools function with your Vinkius HTTP URL for Dagster. Pass the resulting tool list directly to your AutoGen AssistantAgent.

Yes, the MCP tool adapter handles schema conversion, allowing different agents in your AutoGen group chat to invoke `list_runs` or `list_assets` as needed.

The AutoGen agents run a conversation loop to resolve Dagster contradictions. If `list_runs` shows a failure but `list_sensors` shows normal status, they debug the Dagster mismatch together.

Yes, as long as your local Dagster instance is network-accessible. Your AutoGen agents can query it via the secure Vinkius gateway.

All AutoGen tool calls run inside an ephemeral, zero-trust sandbox. Your Dagster pipeline execution data and job schemas are never stored, cached, or used for model training.

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